Reference genes for the normalization of gene expression analysis data

ABSTRACT

The present invention relates to reference genes, primers, and probes for the normalization of gene expression analysis data from blood samples of a patient. The invention further relates to a method for the normalization of gene expression analysis data with the aid of reference genes, primers, or probes.

The present invention relates to genes, in particular a set of reference genes for the normalization of gene expression analysis data, PCR primers derived from the reference genes, probes derived from the reference genes, as well as a method for the normalization of gene expression analyses.

There is a persistent demand to identify genes, in particular from blood cells, which exhibit only minimum variation of expression under different conditions. These so-called “housekeeper” or “housekeeping” genes are utilized as references, internal controls and reference values in the quantification of gene expression and of RNA and mRNA by means of methods such as Northern Blotting, Ribonuclease Protection Assay, capillary electrophoresis, microarrays, and quantitative real-time PCR, and by means of further methods for the direct measurement of transcription and measurement after a previous amplification.

In the following, the terms ‘housekeeper’, ‘housekeeping genes’ and ‘expression control genes’ shall be subsumed under the term ‘reference genes’. This simplification is carried out for reasons of easier reading while not constituting any restriction of the invention.

A normalization of quantitative data with the aid of reference genes possesses numerous possible applications. The reference genes allow an identification of genes whose activity is regulated differentially in different pathological conditions, as well as the development of diagnostics based thereon.

A reference gene is a gene that exhibits minimum change of expression and transcription across different RNA samples and thus serves als a control, or reference, for the measurement of variable gene activities across different samples. There is no gene that exhibits unchanged activity across all tissues. Accordingly there is a high demand for new reference genes, in particular for blood, as expression values from blood are employed in diagnosis.

Although various control genes are known from literature [1], no reference genes and transcripts thereof nor their combined use for the normalization of gene expression and transcription from full blood samples and blood cells are known. Transcripts (also, mRNA and microRNA as well as additional RNA) having a constant concentration in blood cells and in cells from organs and peripheral tissue that are located in full blood represent a precondition for the normalization of gene activities and for the determination of the changes of other gene activities, and thus a precondition for blood-based diagnostics. Likewise, various studies for the measurement of gene activity for the diagnosis/prognosis of SIRS and sepsis have already been published, for example [2, 3], however a use and quantification of these gene activity signals by means of reference genes from blood have not been described yet.

Accordingly there is a demand for reference genes from blood and blood cells that are robust and possess stability to allow normalization and quantification of the gene expression of disease-specific genes or gene clusters.

The invention disclosed in the present patent application starts out from the discovery that gene activities of different genes occurring in blood cells in samples of an individual in whom pathological phenomena typical for sepsis (in accordance with the definition in [4]) are detected, do not differ from the gene activities of the same genes of individuals in whom no sepsis was diagnosed, and may jointly or singly be used as reference genes for the normalization of gene activities from blood cells and for the determination of concentration of transcripts from blood. This allows the normalization and relative quantification of the activities of other genes, which may be utilized for diagnosis, prognosis, therapy, and follow-up.

The present invention is therefore based on the object of furnishing means and methods furnishing the possibility of a reference point for the differentiation of changes of gene expression brought about by a medical disorder, and thus a diagnosis or follow-up of the therapy.

The invention describes the identification of new reference genes from blood, suitable microarray probes and PCR primers and their use, also in combination, for the normalization of quantitative expression data from blood and blood cells in microarrays, real-time PCR assays, and other systems with or without amplification and with different visualization options for determination, as well as their utilization for the diagnosis of changes in local inflammations of different localization brought about by a medical disorder and in the systemic reaction thereto, such as SIRS, sepsis, severe sepsis with organ failure.

In these examinations the normalization of gene expression analyses is of crucial importance. For the purposes of the present invention, normalization is intended to be understood as follows:

“Normalization is understood as rendering the measurements of different arrays or PCR or in particular RT-PCR experiments comparable by reducing or removing the technical variability. Within these experiments there exists a multiplicity of sources capable of falsifying the measurements. Possible technical sources of interference are: different efficiency in reverse transcription, labelling or hybridization reactions, as well as problems with the arrays, batch effects in reagents, or lab-specific conditions.”

The method of the invention is characterized in that it is possible to differentiate, in a blood sample of an individual, the activity of one or several genes to be examined through the determination of the presence and quantity of the gene product relative to the quantities of the gene products of the reference genes between SIRS and sepsis.

What is disclosed for this purpose are reference genes and gene sequences from blood and blood cells as well as primers and probes derived therefrom, which may be used for the determination, visualization and normalization and quantification of gene activities and transcripts. The sequences of the oligonucleotide probes in preferred implementation are set forth in Table 1 and correspond to the one in the annexed sequence protocol SEQ ID NO: 1 to SEQ ID NO: 7, primer sequences used in accordance with Table 2 correspond to the one in the annexed sequence protocol SEQ ID NO: 8 to SEQ ID NO: 21. The sequences of the oligonucleotide probes may also assume other sequences, in preferred implementation having a length of 50-100 nucleotides, which specifically bind transcripts of the genes set forth in Table 3 with sequences SEQ ID NO: 22 to SEQ ID NO: 97. The sequences used in amplification methods such as PCR may have a random length as long as they support the desired enzymatic manipulation and amplification.

TABLE 1 DNA Oligonucleotide Probes Gene Symbol SEQ ID NO: ITGAL 1 SNAPC1 2 CASP8 3 C7 4 PPARD 5 IL18 6 F3 7

TABLE 2 Forward and Reverse DNA Primers Forward Primer Reverse Primer Gene Symbol SEQ ID NO: SEQ ID NO: ITGAL 8 15 SNAPC1 9 16 CASP8 10 17 C7 11 18 PPARD 12 19 IL18 13 20 F3 14 21

TABLE 3 Reference Genes (RNA Sequences) GenBank Accession Number SEQ ID NO: NM_024081 22 AA398364 23 N34546 24 AA659421 25 AA682479 26 AK024118 27 AA923316 28 BM309952 29 AI093653 30 AI131415 31 AI263527 32 AA282242 33 CR740270 34 BG191861 35 AI301257 36 AI310464 37 AW964023 38 AI351933 39 AA100540 40 AI362368 41 AI817134 42 AI381377 43 AI520967 44 AA253470 45 AI559304 46 AI565002 47 AI587389 48 AI609367 49 AI635278 50 AI702056 51 AI707917 52 AI733176 53 AI769053 54 AI798545 55 AI801425 56 AI801595 57 AI809873 58 AI862063 59 AI923251 60 AI925556 61 AI932551 62 AI932884 63 AI933797 64 AI933967 65 AI935874 66 H06263 67 H22921 68 H54423 69 N22551 70 N73510 71 R06107 72 R42511 73 R43088 74 NM_181705 75 R92455 76 R93174 77 T77995 78 T79815 79 T83946 80 T95909 81 T98779 82 AK127462 83 W80744 84 W86575 85 AJ297560 86 NM_001562 87 BU629240 88 NM_001228 89 NM_001993 90 NM_002209 91 NM_002392 92 NM_000587 93 NM_004379 94 BC002715 95 NM_003082 96 AA664688 97

The primers in Table 2 may be used for producing amplification products containing the desired region (sequence) of the named genes. In customary implementation, the product has a length of 150-200 nucleotides.

The reference genes may be used singly or in combination of several ones. Customarily the activity of reference genes as presently described may be determined with the aid of hybridization probes for microarrays or PCR primers and real-time PCR. The reference genes and their expression products may, however, also be determined after amplification by other methods that are known to the person having skill in the art, such as e.g., NAsRA (Nucleic Acid Sequence-Based Amplification) and in various combination. They may also be determined with the aid of a number of further methods or visualization options such as, e.g., with the aid of monoclonal antibodies. Primers and probes may be employed for the gene, the expression product (mRNA), or intermediate expression products which are not processed entirely into mRNA.

In other embodiments the primers and probes bind a specific region of the presently disclosed reference genes or of transcripts thereof. The probes and primers may, however, interact with any region of the presently disclosed gene sequences or sequences transcribed therefrom. The primers and probes may interact via successive base pairing, however need not necessarily interact with the complete complementary sequence. The buffer compositions, salt concentrations, washing steps and temperatures may here be selected to be variable.

Likewise, these changes of the reference genes and of the test genes may be compared to the expression values (or data derived therefrom such as, e.g., average values) of one or several reference samples that are not determined concurrently with the target sample.

One embodiment of the invention is characterized in that expression values are determined by using reference genes in accordance with Table 3 as well as nucleic acids and transcripts of these reference genes from blood and from blood cells as reference genes by way of comparison of the expression values to one or several test nucleic acids and by quantification relative to the test nucleic acid.

One further embodiment of the invention is characterized in that nucleic acids and DNA probes having the sequences according to Table 1 and their binding of RNA, including microRNA, and of transcripts (RNA or mRNA) in blood or from blood cells of genes according to Table 3 in solution or immobilized on surfaces or particles or beads and the use of the bound transcripts of these genes are used for normalization by comparison of the bound quantities (expression values) of the nucleic acids to one or several test nucleic acid(s) bound to probes, and for quantification relative to the bound test nucleic acid.

One embodiment of the invention is characterized in that the method for ex vivo, in vitro differentiation between SIRS and sepsis (both in correspondence to [4]) based on establishing a relation between the RNA quantities from reference gene and test gene includes the following steps:

-   -   a) isolating reference gene RNA and test gene RNA from a blood         sample,     -   b) marking the reference gene RNA and test gene RNA with a         detectable marker and contacting with the DNA under         hybridization conditions, the DNA being a gene fragment or         oligonucleotide which specifically binds transcripts,         amplification products, or in vitro transcripts of reference         genes,     -   c) quantitatively detecting the marking signals of the reference         gene RNA and test gene RNA in accordance with b), and     -   d) comparing the quantitative data of the marking signals in         order to give a statement whether a specific gene or gene         fragment are expressed more strongly or more weakly in         comparison with the signals of the reference genes.

Another embodiment of the invention is characterized in that the reference gene RNA is hybridized with the DNA prior to measurement of the test gene RNA, and the marking signals of the control RNA/DNA complex are detected, in a given case transformed further, and in a given case stored in the form of a calibration curve or table.

Another embodiment of the invention is characterized in that RNA of the reference genes or parts thereof are identified and quantified by way of sequencing or partial sequencing, for instance by way of pyrosequencing.

Another embodiment of the invention is characterized in that mRNA or microRNA is used as reference gene RNA.

Another embodiment of the invention is characterized in that the DNA is disposed, in particular immobilized, for specific binding of the reference gene RNA or its in vitro transcripts in predetermined regions on a support having the form of a microarray.

Another embodiment of the invention is characterized in that the biological sample is that of a human being.

These sequences having SEQ ID NO: 1 to SEQ ID NO: 97 are encompassed in the scope of the present invention and are disclosed in detail in the annexed, 70-page sequence protocol including 107 sequences which thus forms part of the invention.

Another embodiment of the invention is characterized in that the immobilized or free probes are marked with sequences corresponding to Table 1. For this embodiment, self-complementary oligonucleotides, so-called molecular beacons, are employed as probes. At their ends they carry a fluorophore/quencher pair, so that in the absence of a complementary sequence they are present in a folded hairpin structure and furnish a fluorescence signal only with a corresponding sample sequence. The hairpin structure of the molecular beacons is stable until the sample hybridizes at the specific catcher sequence, resulting in a change of conformation and thus also in a release of the reporter fluorescence.

Another embodiment of the invention is characterized in that at least 1 to 14 nucleic acid probes or their complements are used for binding the transcripts, or the complements thereof, of the reference genes.

Another embodiment of the invention is characterized in that the synthetic analoga of the reference genes, or the synthetic oligonucleotides which bind the transcripts of the reference genes, in particular include approx. 60 base pairs.

Another embodiment of the invention is characterized in that the genes listed as DNA in the claims are replaced by sequences derived from their RNA, synthetic analoga, aptamers, and peptidonucleic acids.

Another embodiment of the invention is characterized in that a radioactive marker, in particular ³²P, ¹⁴C, ¹²⁵I, ³³P or ³H, is used as a detectable marker.

Another embodiment of the invention is characterized in that a non-radioactive marker, in particular a dye or fluorescence marker, an enzyme marker or immune marker, and/or quantum dots or an electrically measurable signal, in particular changes of potential and/or conductivity and/or capacity in hybridizations, is used as a detectable marker.

Another embodiment of the invention is characterized in that the sample RNA and reference gene RNA and/or enzymatic or chemical derivatives carry the same marking.

Another embodiment of the invention is characterized in that the test gene RNA and reference gene RNA and/or enzymatic or chemical derivatives carry different markings.

Another embodiment of the invention is characterized in that the DNA probes are immobilized on glass or plastic.

Another embodiment of the invention is characterized in that the single DNA molecules are immobilized through a covalent binding to the support material.

Another embodiment of the invention is characterized in that the single DNA molecules are immobilized to the support material by means of electrostatic and/or dipole-dipole and/or hydrophobic interactions and/or hydrogen bridges.

Another embodiment of the invention consists in the use of recombinant or synthetically produced, specific reference gene nucleic acid sequences, partial sequences singly or in partial quantities as a calibrator in sepsis assays and/or for the evaluation of effect and toxicity in active agent screening and/or for the production of therapeutics and of substances and mixtures of substances intended as a therapeutic, for the prophylaxis and treatment of SIRS and sepsis.

The person having skill in the art will be aware that the single features of the invention as set forth in the claims may be combined at will without any restrictions.

Reference genes within the meaning of the invention are understood to be any derived DNA sequences, partial sequences and synthetic analoga (e.g., peptidonucleic acids, PNA). The description of the invention relating to determination of the gene expression on the RNA level does not constitute a restriction but only an exemplary application.

One application of the method of the invention resides in the normalization of measurement data of the differential gene expression from full blood, for instance for the differentiation between SIRS and sepsis and their degrees of severity (both in correspondence to [4]). To this end, the RNA of the reference genes is isolated from the full blood of corresponding patients and from a control sample of a healthy test person or non-infectious patient. The RNA is subsequently marked, for instance radioactively with ³²P, or with dye molecules (fluorescence). Any molecules and/or detection signals that are known for this purpose in the prior art may be utilized as marking molecules. Corresponding molecules and/or methods are equally known to the person having skill in the art.

The RNA thus marked is subsequently hybridized with DNA molecules immobilized on a microarray. The DNA molecules immobilized on the microarray represent a specific selection of the genes in accordance with the present invention for the normalization of gene expression data in the differentiation of SIRS and sepsis.

The intensity signals of the hybridized molecules are then measured by suitable measurement apparatus (Phosporimager, microarray scanner) and analyzed by further software-supported evaluations. The expression ratios between the test genes of the patient sample and the reference genes are determined from the measured signal intensities. From the expression ratios of the under- and/or over-regulated genes it is possible to draw conclusions as to the differentation between SIRS and sepsis as in the experiments represented hereinbelow.

Another application of the gene activities determined by way of microarray analysis with subsequent quantification for the normalization of gene expression data consists in the application for the differentiation of SIRS and sepsis for the further electronic processing for the purpose of producing software for diagnostic purposes (e.g., for the determination of the localization of an inflammation and for assessing the severity of affliction of an individual immune response particularly with infections, also in the framework of patient data management systems or expert systems) or for modelling cellular signal transmission paths.

The following applies to the implementation of the evaluation of the microarrays for the purposes of the present patent application:

Microarray Experimental Description

(According to the Minimum Information About a Microarray Experiment [MIAME] Checklist—New edition January 2005, based on Brazma A et al., Minimum information about a microarray experiment (MIAME)—toward standards for microarray data, Nature Genetics 29, 365-371 (2001) [17], the contents of which are fully incorporated herein by way of reference)

Reading in of Slides/Scanner Technical Specifications

a) Scanner: GenePix 4000B confocal incident-light fluorescence scanner (Axon Instruments) b) Scanning software: GenePix Pro 4.0 c) Scanning parameters: Laser power: Cy3 channel - 100% Cy5 channel - 100% PMT voltage: Cy3 channel - 700 V Cy5 channel - 800 V d) Spatial resolution (pixel space) - 10 μm. Reading Out and Processing of Data

In the framework of the experiments, more than 1,000 blood samples of patients were hybridized. Each RNA pair (patient versus comparative RNA) was co-hybridized on a microarray. The patient RNA was marked with a red fluorescent dye, and the comparative RNA with a green fluorescent dye. The digitized images of the hybridized array were evaluated with the GenePix Pro 4.0 or 5.0 software by Axon Instruments. For spot detection, signal quantification and evaluation of the spot quality, the GenePix™ analysis software was used. The spots were marked, in accordance with the settings in the GenePix™ software, as 100=“good”, 0=“found”, −50=“not found”, −75=“absent”, −100=“bad.” The raw data was stored in a corresponding *.gpr file.

Normalization, Transformation and Data Selection Method

e) Transformation and Normalization of the Signal Data

For the normalization and variance-stabilized transformation of the raw data the method of Huber et al. [5] was used, in which the additive and multiplicative errors are estimated block by block. About 75% of all the spots are utilized for this. The signals are then transformed by the arsinh function. (Thus, the transformed ratio of ±0.4 about corresponds to a 1.5-fold change {for large numbers, arsinh (x) is nearly identical with Ln (2x)}.

Rocke D M, Durbin B, A model for measurement error for gene expression arrays, J Comput Biol. 2001; 8(6):557-69 [18], have developed a model for estimating the measurement error in gene expression arrays as a function of the expression level, the contents of which are hereby fully incorporated by way of reference. This error model in combination with further analysis methods, data transformations and weightings, already allows a more accurate comparison of the gene expression data and furnishes guidelines for background analysis, determination of confidence intervals and processing of the analysis data for their multivariate further processing or analysis, respectively.

Based on the above-mentioned error model by Rocke and Durbin [18], Huber W, Heydebreck A, and Sueltmann H, Variance stabilization applied to microarray data calibration and to the quantification of differential expression, Bioinformatics. 2002; 18 Suppl 1:pp. 96-104 [19], have developed a statistical model for microarray gene expression data, the contents of which are hereby fully incorporated by way of reference. The model includes a data calibration, the quantification of different expression levels, as well as the quantification of the measurement error. In this regard, Huber et al. [19] derived a data transformation for signal intensity measurements and a difference statistic, which results in a variance stabilization and normalization of a set of signal data across its entire intensity range by using the area function arsinh. This method was in particular demonstrated on microarray gene expression data but is also transposable to other methods for gene expression measurement in the framework of the present invention.

Hereby the dependency of variance on signal intensity, which is frequently observed in the evaluation of signals, is compensated by the mentioned transformation with the aid of the area function.

f) Filtration

The technical replicates (multiple spots of a same sample) on the microarray are filtered out from the corrected and transformed signal intensities in dependence on their spot quality. For each spot the replicates having the highest characterization are selected, and the associated signal intensity is averaged. The expression of spots having exclusively non-measurable replicates are designated “NA” (not available).

Another application of the method of the invention consists in measuring the differential gene expression for the determination, concurrently with the therapy, of the probability that patients will respond to the projected therapy, and/or for the determination of the response to a specialized therapy and/or to the fixation of the end of therapy in the sense of a “drug monitoring” in patients with SIRS and sepsis and their degrees of severity. To this end, the RNA (test RNA and control RNA) is isolated from the patient's blood samples that were collected at temporal intervals. The different RNA samples are marked jointly and hybridized with selected test genes and with reference genes immobilized on a microarray. From the expression ratios between single or several reference genes and test genes such as, e.g., TNF alpha it is thus possible to evaluate the probability that patients will respond to the projected therapy and/or whether the begun therapy is effective and/or how much longer the patients will have to be therapied correspondingly and/or whether the maximum therapy effect has already been reached with the dose and duration employed. Another application of the method of the invention consists in the use of the RNA of the genes in accordance with the invention for obtaining quantitative information through hybridization-independent methods, in particular enzymatic or chemical hydrolysis, Surface Plasmon Resonance methods (SPR methods), subsequent quantification of the nucleic acids and/or of derivatives and/or fragments of these.

The transcripts of reference genes amplified and quantified by means of PCR (and also additional amplification methods such as NASBA) constitute another embodiment in accordance with the present invention for the normalization of gene expression data in the differentiation of SIRS and sepsis and their degrees of severity. The intensity signals of the amplified transcripts are then measured by suitable measurement apparatus (PCR fluorescence detector) and analyzed with the aid of further software-supported evaluations. From the measured signal intensities the expression ratios between the test genes of the patient sample and the reference genes are determined. From the expression ratios of the under- and/or over-regulated genes it is possible—as in the experiments represented hereinbelow—to draw conclusions as to the differentiation between SIRS and sepsis and their degrees of severity.

Another application of the method of the invention consists in the use of the gene activities determined by way of PCR or other amplification methods with subsequent quantification for the normalization of gene expression data for the differentiation of SIRS and sepsis and their degrees of severity for the electronic further processing for the purpose of producing software for diagnostic purposes (e.g., for the determination of the focus of an inflammation and for an assessment of the severity of an individual immune response in particular with bacterial infection, also in the framework of patient data management systems or expert systems) or for modelling cellular signal transmission paths.

Another application of the method of the invention consists in the determination of an mRNA quantity in a sample, including a) isolation of the nucleic acids, b) a measurement of the expression value of one or several nucleic acids selected from SEQ ID NO: 22 to SEQ ID NO: 97; c) a comparison of the expression values of the selected nucleic acids to known percentage values of the nucleic acids in the total quantity of mRNA; d) extrapolation of the expression values of one or several nucleic acids selected from SEQ ID NO: 22 to SEQ ID NO: 97 to the total quantity of mRNA, and d) determination of the total quantity of mRNA in the sample.

Another application of the method of the invention consists in the normalization of an mRNA quantity—in a given case amplified—in several samples, including a) a comparison of the expression values of one or several nucleic acids selected from SEQ ID NO: 22 to SEQ ID NO: 97 across various samples; b) deriving a value for the normalization of expression values of one or several nucleic acids selected from SEQ ID NO: 22 to SEQ ID NO: 97 across several samples; and c) a normalization of the expression of other nucleic acids that were isolated from several samples, based on step b).

The invention may further relate to a kit containing a selection of sequences in accordance with SEQ ID NO: 22 to SEQ ID NO: 97 and/or gene fragments thereof including at least 1-100, in preferred embodiments 1-5 and 1-10 nucleotides, for the in vitro determination of gene expression profiles in a patient sample, for the use as reference genes.

The invention may further also relate to a kit containing a selection of hybridization probes in accordance with SEQ ID NO: 1 to SEQ ID NO: 7 and/or gene fragments thereof including at least 50 nucleotides for the in vitro determination of gene expression profiles in a patient sample, for the use as reference genes.

The invention may equally relate to a kit containing a selection of primer probes in accordance with SEQ ID NO: 8 to SEQ ID NO: 21 and/or gene fragments thereof including at least 15 nucleotides for the in vitro determination of gene expression profiles in a patient sample, for the use as reference genes.

In its broadest and most general formulation, the present invention relates to the following embodiments:

A) At least one reference gene for the normalization of gene expression analysis data from blood samples of a patient, wherein the reference gene is selected from the following RNA sequences: SEQ ID NO: 22 to SEQ ID NO: 97, in particular SEQ ID NO: 87, SEQ ID NO: 89, SEQ ID NO: 90, SEQ ID NO: 91, SEQ ID NO: 93, SEQ ID NO: 95, and SEQ ID NO: 96.

B) At least one primer, derived from the reference genes in accordance with A) for the normalization of gene expression analysis data based on nucleic acid amplification, from blood samples of a patient, wherein the primer is selected from the following DNA sequences: SEQ ID NO: 8 to SEQ ID NO: 21.

C) At least one probe, derived from the reference genes in accordance with B) for the normalization of gene expression analysis data from blood samples of a patient, wherein the set of probes includes the following DNA sequences: SEQ ID NO: 1 to SEQ ID NO: 7, as well as their complementary nucleic acid sequences.

D) A method for the normalization of gene expression analysis data with the aid of at least one control nucleic acid selected from the reference genes in accordance with A) or a set of primers in accordance with B) or a set of probes in accordance with C), wherein

-   -   a) at least one gene expression analysis assay is carried out in         vitro on blood samples of a patient;     -   b) at least one control nucleic acid in the same assay is         jointly examined as a basis for the normalization of the gene         expression analysis data of the samples to be examined;     -   c) signals from the gene expression analyses are detected, which         reflect the degree of the gene expression of a plurality of         genes and of the at least one control nucleic acid;     -   d) the signal data obtained in step c) is subjected to a         mathematical transformation in order to at least weaken the         technical variability of the signal data; and thereby     -   e) to normalize the signal data of the samples to be examined.

E) Preferred embodiments of the method in accordance with D) are:

A method according to D), wherein the mathematical transformation of the signal data is carried out by means of the arsinh or by means of a logarithmic approach;

and/or

the gene expression assay is selected from:

-   -   f) isolation of nucleic acids from a blood sample;     -   g) in a given case a co-amplification of a set of control         nucleic acids and the nucleic acids to be tested; and     -   h) probe hybridization;         and/or         the nucleic acids include mRNA or microRNA;         and/or         the nucleic acids are amplified by means of PCR, real-time PCR,         NASBA, TMA, or SDA;         and/or         the expression values of the control and test nucleic acids are         determined by means of hybridization methods;         and/or         the measurement of the expression values of the control and/or         test nucleic acids takes place in solution or on nucleic acids         immobilized on a support;         and/or         the support is a microarray, particle, bead, glass, metal or         membrane;         and/or         the control and/or test nucleic acids are indirectly coupled to         the support with the aid of other binding partners such as         antibodies, antigenes, oligonucleotides, molecular beacons, or         enzymes;         and/or         the expression values of the control and test nucleic acids         determined in vitro from a sample of a patient are utilized as         input parameters for the production of software for the         description of the individual prognosis of a patient, for         diagnostic purposes, for therapy decisions and/or patient data         management systems.

F) A use of at least one control nucleic acid, selected from the reference genes in accordance with A) or a primer in accordance with B) or a probe in accordance with C), for the normalization of a gene expression analysis method for the diagnosis of disorders involving systemic immune reaction.

G) Preferred embodiments of the use in accordance with F) are:

A use according to F), wherein the disorders are selected from: sepsis, severe sepsis, septic shock, or multiple organ failure;

and/or

in a method for in vitro diagnosis of SIRS, sepsis, severe sepsis, septic shock or multiple organ failure in an individual by using sets of control nucleic acids and test nucleic acids, the expressions of which are specific for SIRS or sepsis, including the following steps:

-   -   a) concurrent isolation of the control and test nucleic acids         from a sample of the individual,     -   b) in a given case, amplification of the control and test         nucleic acids,     -   c) determination of the expression values of the control and         test nucleic acids,     -   d) a normalization of the gene expression of the test nucleic         acids based on the expression values of the control nucleic         acids,     -   e) determination whether the normalized expression values of the         test nucleic acid have reached a specific value for SIRS,         sepsis, severe sepsis, septic shock, or multiple organ failure.

The following also fundamentally applies for data transformation/normalization in the framework of the present invention:

1st Variant (suggested for normalization in PCR experiments or also in small diagnostic arrays):

The signals of the reference genes are aggregated, and subsequently the ratio of the signals of the test genes to the aggregated signal of the reference genes is calculated. In the case of logarithmed signals the ratio then consists of the difference.

2nd Variant (e.g., Huber et al. [19] in “whole genome” approaches or large arrays): The signals of the reference genes are used to estimate the parameters of a suitable transformation or the transformation itself.

This transformation is then applied to the test genes

Further advantages and features of the present invention become evident from the description of practical examples.

PRACTICAL EXAMPLE 1 Identification of Reference Genes from Blood and from Blood Cells

Measurement of the Gene Expression:

The gene expression of 372 intensive therapy unit patients (ITU patients) was measured. All of the patients were under intensive-care medical treatment. A maximum of seven ITU days was considered for each patient. In patients with more than seven ITU days, seven days were selected randomly. All in all, the data of 1261 microarray experiments entered the analyses.

Selected characteristics of the patients are represented in Tables 4 and 5. Information is provided with regard to age, sex, and ACCP/SCCM categories. The total RNA from cell lines SIG-M5 served as reference samples. All of the patient samples were each co-hybridized with the reference sample on one respective microarray.

TABLE 4 General data of the patients No. of patients (microarrays) 372 (1261) Mortality 94 (25.3%) Sex [F/M] 113/259 Age in years 68 (15) APACHE-II 16 (9) SAPS-II 32 (15) SOFA 8 (4) Duration of hospitalization in days 8 (22) The respective indications are the median and the Inter-Quartile Range (IQR) in parentheses

TABLE 5 Indications subject to operations regarding the as-is analysis (multiple entries possible) Indication No. of patients Coronary vessels 153 Heart valves 65 Gastrointestinal 34 Thorax 17 Polytrauma 13 Peripherala hear vessels 8 Uro-genital 8 Neurosurgery 6 Experimental Description: Taking Blood and RNA Isolation

The patients' full blood was taken from the patients in the intensive care unit by means of the PAXGene Kit in accordance with the manufacturer's (Qiagen) specifications. Following taking of the full blood, the total RNA of the samples was isolated by using the PAXGene Blood RNA Kit in accordance with the manufacturer's (Qiagen) specifications.

Cell Cultivation

For the cell cultivation (control samples) 19 cryocell cultures (SIGM5) (frozen in liquid nitrogen) were utilized. The cells were each inoculated with 2 ml of Iscove's Medium (Biochrom AG) supplemented with 20% fetal calf serum (FCS). The cell cultures were then incubated for 24 hrs at 37° C. under 5% CO₂ in 12-well plates. Then the contents of 18 wells were divided into 2 parts each having a same volume, so that finally 3 plates of a same format (total of 36 wells) were available. Cultivation was then continued for 24 hrs under the same conditions. After this, the resulting cultures of 11 wells of each plate were united and centrifuged (1000×g, 5 min, room temperature). The supernatant was discarded, and the cell pellet was dissolved in 40 ml of the above-identified medium. These 40 ml of dissolved cells were evenly divided into two 250-ml test tubes and following 48 hrs of incubation and addition of 5 ml of the above-identified medium were incubated once more. Of the remaining 2 ml of the two remaining plates, 80 μl were placed in empty wells of the same plates which had already been prepared in advance with 1 ml of the above-identified medium. After 48 hrs of incubation, only one of the 12 well plates was processed as follows: From each well 500 μl was taken and united. The resulting 6 ml was placed in a 250-ml test tube containing approx. 10 ml of fresh medium. This mixture was centrifuged at 1000×g for 5 minutes at room temperature and dissolved in 10 ml of the above-identified medium. The subsequent cell count yielded the following result: 1.5×10⁷ cells per ml, 10 ml total volume, total number of cells: 1.5×10⁸. As the cell number was not sufficient yet, 2.5 ml of the above-identified cell suspension was placed in 30 ml of the above-identified medium in a 250-ml (75 cm²) test tube (altogether 4 test tubes). After an incubation time of 72 hrs, 20 ml each of fresh medium was placed in the test tube. Following 24 hrs of incubation, the cell count was performed in accordance with the above description and resulted in a total cell number of 3.8×10⁸ cells. In order to obtain the desired cell number of 2×10⁶ cells, the cells were resuspended in 47.5 ml of the above-identified medium in 4 test tubes. After an incubation period of 24 hrs, the cells were centrifuged and washed twice with phosphate buffer without Ca²⁺ and Mg²⁺ (Biochrom AG).

Isolation of the total RNA takes place by means of the NucleoSpin RNA L Kit (Machery&Nagel) in accordance with the manufacturer's specifications. The above-described procedure was repeated until the required cell number was obtained. This was necessary in order to obtain the required amount of 6 mg of total RNA, approximately corresponding to an efficiency of 600 μg of RNA per 10⁸ cells.

Reverse Transcription/Marking/Hybridization

Following taking of the full blood, the total RNA of the samples was isolated and examined as to its quality by using the PAXGene Blood RNA Kit (PreAnalytiX) in accordance with the manufacturer's specifications. From each sample 10 μg of total RNA was aliquoted and rewritten, together with 10 μg of total RNA from SIGM5 cells as reference RNA, into complementary DNA (cDNA) with Reverse Transcriptase Superscript II (Invitrogen), and the RNA was subsequently removed from the batch by alkaline hydrolysis. In the reaction batch a part of the dTTP was replaced with aminoallyl-dUTP (AA-dUTP) in order to allow coupling of the fluorescent dye to the cDNA later on.

Following purification of the reaction batch, the cDNA of the samples and controls were marked covalently with the fluorescent dyes Alexa 647 and Alexa 555 and hybridized on a microarray of the company SIRS-Lab. On the microarray used there are 5,308 immobilized polynucleotides having a length of 55-70 base pairs each representing one human gene, and control spots for quality assurance. One microarray is subdivided into 28 sub-arrays having a raster of 15×15 spots.

Hybridization and subsequent washing and drying, respectively, were carried out in the hybridization station HS 400 (Tecan) in accordance with the manufacturer's specifications during 10.5 hrs at 42° C. The hybridization solution used consists of the respective marked cDNA samples, 3.5×SSC (1×SSC contains 150 mM sodium chloride and 15 mM sodium citrate), 0.3% sodium dodecyl sulfate (V/V), 25% formamide (V/V), and 0.8 μg μl-1 cot-1 DNA, yeast t RNA and poly-A RNA each. The subsequent washing of the microarrays was carried out with the following program at room temperature: 90 seconds each rinsing with washing buffer 1 (2×SSC, 0.03% sodium dodecyl sulfate), with washing buffer 2 (1×SSC), and finally with washing buffer 3 (0.2×SSC). Then the microarrays were dried under a nitrogen flow at a pressure of 2.5 bars at 30° C. during 150 seconds.

Following hybridization, the hybridization signals of the microarrays were read out with the aid of a GenePix 4000B scanner (Axon), and the expression ratios of the differenciated expressed genes were determined with the aid of the software GenePix Pro 4.0 (Axon).

Evaluation:

For the evaluation, the mean intensity of a spot was determined as the median value of the associated spot pixel.

Pre-Selection of Gene Samples:

For a first pre-selection of the gene probes the correction of systematic errors was performed in accordance with the approach of Huber et al. [5]. Additive and multiplicative bias within a microarray was estimated from 75% of the gene samples present.

Subsequently the normalized and transformed ratios of the signals of the patient samples were calculated versus the general control. I.e., for the j-th gene of the k-th array the calculation yielded the value G _(j,k)=arsinh(Scy5(j,k)−arsinh(Scy3(j,k)) wherein [Scy3(j,k), Scy5(j,k)] designates the related fluorescence signal pair. For all of the gene probes the median of the absolute deviations from the median (MAD), i.e. MAD(G_(j), 1, . . . , G_(j), 1261), was subsequently calculated, and the 10% gene probes having the lowest MAD were selected. As the second criterion for the pre-selection the mean signal intensity arsinh(Scy5(j,k))+arsinh(Scy3(j,k)) was employed. In the further analyses, only gene probes having a median of the mean signal intensity in the so-called dynamic signal range, preferably between 6 and 8 (on the logarithmic scale), were taken into consideration. Selection of the Reference Genes:

For the gene probes selected in advance, relative quantities were calculated by setting the highest expression value to 1. Subsequently the gene stability measure M of Vandesompele et al. [6] was calculated. By means of the stepwise procedure, equally described in Vandesompele et al., in which the gene having the lowest stability is removed in each step, the gene probes were arranged in accordance with their stability. The upper threshold value for the selection of the gene probes was based on the (rounded) value 0.6 for the mean value of the stability measure M (Table 6).

The mathematical definition for the gene stability measure M in accordance with Vandesompele et al. is:

For each combination of two internal reference genes j and k, an array A_(jk) of m elements is given which consists of the log₂-transformed expression ratios a_(ij)/a_(ik) (Equation 1). The paired variation V_(jk) for the reference genes j and k is furthermore defined as the standard deviation of the elements A_(jk) (Equation 2), with SD being the standard deviation. The gene stability measure M_(j) for the reference gene j then is the arithmetical mean of all paired variations V_(jk) (Equation 3):

(For every j,k: [1,n] and j k):

$\begin{matrix} \begin{matrix} {A_{jk} = \left\lbrack {{\log_{2}\left( \frac{a_{1\; j}}{a_{1\; k}} \right)},{\log_{2}\left( \frac{a_{2\; j}}{a_{2\; k}} \right)},\ldots\mspace{14mu},{\log_{2}\left( \frac{a_{mj}}{a_{mk}} \right)}} \right\rbrack} \\ {= \left\lbrack {\log\; 2\left( \frac{a_{ij}}{a_{ik}} \right)} \right\rbrack_{i = {1\rightarrow m}}} \end{matrix} & (1) \\ {V_{jk} = {{SD}\left( A_{jk} \right)}} & (2) \\ {{Mj} = \frac{\sum\limits_{k = 1}^{n}V_{jk}}{n - 1}} & (3) \end{matrix}$

A cluster was determined on 76 specific sequences having unchanged gene activity corresponding to SEQ ID NO: 22 to SEQ ID NO: 97 that are part of the annexed sequence protocol.

TABLE 6 Determined reference genes (RNA base) and their stability values GenBank Accession MAD of the Median of the Stability SEQ ID NO: Number Signal Ratios Mean Intensities M 22 NM_024081 0.200 7.190 0.368 23 AA398364 0.179 6.730 0.385 24 N34546 0.171 6.265 0.401 25 AA659421 0.212 7.127 0.380 26 AA682479 0.218 6.209 0.373 27 AK024118 0.172 6.601 0.457 28 AA923316 0.197 6.891 0.374 29 BM309952 0.205 7.533 0.417 30 AI093653 0.156 7.120 0.355 31 AI131415 0.156 6.881 0.413 32 AI263527 0.173 6.614 0.379 33 AA282242 0.181 6.758 0.381 34 CR740270 0.191 6.360 0.346 35 BG191861 0.191 6.292 0.377 36 AI301257 0.244 6.039 0.401 37 AI310464 0.202 6.229 0.423 38 AW964023 0.204 6.776 0.380 39 AI351933 0.171 6.478 0.414 40 AA100540 0.196 7.180 0.365 41 AI362368 0.199 6.967 0.397 42 AI817134 0.167 6.592 0.362 43 AI381377 0.193 6.179 0.401 44 AI520967 0.188 6.534 0.386 45 AA253470 0.182 7.002 0.365 46 AI559304 0.195 7.408 0.369 47 AI565002 0.182 7.149 0.381 48 AI587389 0.197 7.006 0.355 49 AI609367 0.206 6.648 0.354 50 AI635278 0.200 6.629 0.427 51 AI702056 0.208 6.370 0.391 52 AI707917 0.177 6.392 0.414 53 AI733176 0.209 6.211 0.411 54 AI769053 0.210 7.570 0.383 55 AI798545 0.167 7.289 0.394 56 AI801425 0.174 6.780 0.406 57 AI801595 0.188 7.061 0.409 58 AI809873 0.200 7.207 0.413 59 AI862063 0.173 7.001 0.347 60 AI923251 0.197 7.085 0.359 61 AI925556 0.178 6.924 0.329 62 AI932551 0.177 7.191 0.415 63 AI932884 0.182 7.430 0.409 64 AI933797 0.204 6.834 0.423 65 AI933967 0.193 7.007 0.443 66 AI935874 0.203 7.166 0.388 67 H06263 0.169 7.140 0.337 68 H22921 0.241 6.445 0.408 69 H54423 0.175 7.046 0.385 70 N22551 0.205 6.830 0.387 71 N73510 0.181 7.084 0.388 72 R06107 0.164 7.067 0.352 73 R42511 0.212 6.110 0.371 74 R43088 0.215 6.067 0.398 75 NM_181705 0.208 6.821 0.383 76 R92455 0.203 6.629 0.410 77 R93174 0.211 7.164 0.358 78 T77995 0.201 7.251 0.423 79 T79815 0.197 7.270 0.417 80 T83946 0.196 7.388 0.363 81 T95909 0.177 7.109 0.414 82 T98779 0.186 6.964 0.416 83 AK127462 0.198 6.784 0.367 84 W80744 0.194 6.995 0.364 85 W86575 0.236 6.761 0.438 86 AJ297560 0.175 7.063 0.380 87 NM_001562 0.192 7.021 0.516 88 BU629240 0.214 6.696 0.401 89 NM_001228 0.235 6.286 0.423 90 NM_001993 0.192 6.874 0.451 91 NM_002209 0.201 7.676 0.425 92 NM_002392 0.197 6.969 0.431 93 NM_000587 0.199 6.848 0.334 94 NM_004379 0.222 7.135 0.415 95 BC002715 0.182 6.685 0.502 96 NM_003082 0.214 6.327 0.469 97 AA664688 0.192 6.610 0.396

PRACTICAL EXAMPLE 2 Examination of Stability of the Reference Genes by Means of Gene Expression Examinations of Patients with and without Sepsis

In this practical example we show that the reference genes determined in the first practical example are also stable in the cases of patients with and without sepsis under intensive-care treatment. To this end we considered microarray data of 118 patients. Altogether 394 patient days (microarrays) were analyzed, with a maximum of seven days being considered per patient.

TABLE 7 General data of the patients No. of patients (microarrays) 118 (394) Mortality      31 (26.3%) Sex [F/M] 41/77 Age in years [Median (IQR)] 68.5 (14.8)

TABLE 8 Classification of the patient days according to ACCP/SCCM category, as well as additional diagnostic parameters ITU Patients* SIRS Sepsis Severe sepsis Septic shock No. of days 33 158 24 90 89 SOFA Score 7 (3) 7 (4)   6 (3.25) 8 (4) 10 (3)  No. of ODFs 2 (2) 2 (1) 1.5 (1)   3 (2) 3 (2) PCT [ng/ml] 1.6 (3.8) 1.8 (5.4) 1.2 (5.1) 2.5 (4.9)  6.4 (11.5) CRP [mg/l]  144 (53.9) 112.5 (106.4)  141 (87.1)   133 (105.9) 170 (146) WBC [no/l] 7750 (4075) 11100 (7100)  13350 (8800)  12900 (6675)  16100 (10600) *Patients under intensive medical care who did not develop SIRS or sepsis The respective indications are the median and the Inter-Quartile Range (IQR) in parentheses.

In order to demonstrate the applicability of the reference genes by means of a comparison of SIRS and sepsis patients, the following test genes were selected (cf. Table 9).

TABLE 9 Test genes for the comparison of SIRS and sepsis patients GenBank Accession Name Nummer Literature SEQ ID NO: CARD8 NM_014959  [7] 98 CCBP2 NM_001296  [8] 99 CCL26 NM_006072  [9] 100 FADD NM_003824 [10] 101 IL6R NM_181359 [11] 102 ITGB2 NM_000211 [12] 103 MAPK3 NM_002746 [13] 104 MYD88 NM_002468 [14] 105 TNF NM_000594 [15] 106 TREM1 NM_018643 [16] 107

These test genes are described in the scientific literature in connection with sepsis.

For the statistical analysis, 6 patients with severe SIRS (SIRS+organ dysfunctions) and 9 patients with severe sepsis (sepsis+organ dysfunctions) were selected (Table 10).

TABLE 10 Selected characteristics of the SIRS and sepsis patients Severe SIRS Severe Sepsis No. of patients 6 9 Mortality 0 (0%) 5 (55.6%) Sex [M/F] 4/2 7/2 Age [years] 70.5 (7) 74 (7) SOFA Score 8 (2.25) 10 (4) No. of ODFs 3.5 (1.75) 3 (1) PCT [ng/ml] 3.1 (5.5) 28.2 (38.8) CRP [mg/l] 71.2 (15.6) 206 (180) WBC [no/l] 14250 (3800) 15800 (4600) The respective indications are the median and the Inter-Quartile Range (IQR) in parentheses.

Normalization of the ten test genes was carried out by means of the following five, randomly selected reference genes. The method of Vandesompele et al. [6] was used (Table 11).

TABLE 11 Selected reference genes (Set 1) GenBank Accession Nummer SEQ ID NO: AI263527 32 AW964023 38 AI933797 64 T98779 82 NM_004379 94

A comparison by means of the two sample t-test yields the following result (Table 12).

TABLE 12 Gene activity of the test genes normalized with Set 1 of the reference genes Gene symbol SEQ ID NO: Mean SIRS Mean Sepsis p-Value CARD8 98 1.85 4.32 0.045 CCBP2 99 1.25 2.69 0.004 CCL26 100 1.52 2.69 0.041 FADD 101 1.26 3.45 0.028 IL6R 102 1.58 2.15 0.175 ITGB2 103 1.04 2.60 0.074 MAPK3 104 1.26 2.49 0.052 MYD88 105 1.11 2.34 0.025 TNF 106 1.41 2.47 0.055 TREM1 107 1.09 1.52 0.154

In order to demonstrate the repeatability of the results, the statistical comparison was repeated, with reference genes (Set 2) again being selected randomly (Table 13)

TABLE 13 Reference genes (Set 2) GenBank Accession Nummer SEQ ID NO: AI609367 49 AI862063 59 H06263 67 R92455 76 BC002715 95

Following normalization by means of the method of Vandesompele et al., we obtain the following results for the two sample t-test (Table 14):

TABLE 14 Gene activity of the test genes normalized with Set 2 of the reference genes Gene symbol SEQ ID NO: Mean SIRS Mean Sepsis p-Value CARD8 98 1.67 3.71 0.029 CCBP2 99 1.15 2.35 0.001 CCL26 100 1.37 2.34 0.033 FADD 101 1.15 2.98 0.015 IL6R 102 1.44 1.88 0.210 ITGB2 103 0.97 2.27 0.050 MAPK3 104 1.15 2.34 0.065 MYD88 105 1.03 2.05 0.028 TNF 106 1.28 2.20 0.057 TREM1 107 0.99 1.34 0.145

The results indicate very good repeatability of the results. In both comparisons identical markers at the 5% or 10% level, respectively, are significant.

PRACTICAL EXAMPLE 3 Determination of the Stability Values of Selected Reference Genes Through their Specific Primer by Means of Real-Time PCR

RNA Isolation

RNA was isolated from full blood with the aid of the PAXgene Kit (PreAnalytiX) in accordance with the manufacturer's specifications.

Quantitative Reverse Transcriptase-PCR (RT-PCR)

By means of reverse transcription, mRNA was rewritten to cDNA with the aid of an oligo-dT primer independently of its sequence. The cDNA strands formed in the process complementarily to the mRNA used were subsequently used as templates for various PCR reactions.

a) For the batch, the following components were pipetted together:

-   -   5 μg concentrated RNA     -   10 μl H₂O     -   1 μl dNTP (dGTP, dATP, dCTP, dTTP)     -   1 μl oligo dT (0.5 μg/μl)         b) 5 min at 70° C., subsequently 5 min on ice         c) The following mix was added afterwards:     -   4 μl RT buffer     -   2 μl 0.1M DTT     -   1 μl RNase out (RNase inhibitor)     -   1 μl SuperScript reverse transcriptase         d) incubate during 1 h at 42° C.         e) incubate during 15 min at 70° C.         Polymerase Chain Reaction

The selected DNA portion was amplified with the aid of the PCR and subsequently quantified, to thereby determine the strength of the gene expression of the reference genes:

For the PCR, the AccuPrime Taq DNA Polymerase System by invitrogen was used.

For a 25-μl batch, the following components are pipetted together into a 200-μl tube:

-   -   2.5 μl 10× AccuPrime PCR Buffer I     -   20 μl RNase free H₂O     -   1 μl Template DNA 1:10 diluted (approx. 0.82 ng/μl)     -   1 μl Primer mix (0.5 μl forward-/reverse-primer each,         corresponding to Table 2)     -   0.5 μl AccuPrime Taq DNA polymerase

The following program is performed in the real-time PCR thermocycler (corbett research RG 3000):

94° C. 2 min 94° C. 30 sec 58° C. 30 sec 30 cycles 68° C. 1 min 68° C. 2 min

At first the template DNA was denaturated completely at 94° C. and the enzyme was activated. This was followed by 30 amplification cycles consisting of denaturation at 94° C., annealing at 58° C., and elongation at 68° C. Subsequent to the PCR, the samples were transferred onto a 1.5-% agarose gel in order to examine correctness of the products by way of fragment sizes.

TABLE 15 Stability values of selected reference genes (RNA base) determined by specific primer and real-time PCR SEQ ID NO: GenBank Accession Number Stability M 87 NM_001562 1.1028295 89 NM_001228 1.0377301 90 NM_001993 1.9214240 91 NM_002209 1.1226082 93 NM_000587 1.1679851 95 BC002715 1.1285312 96 NM_003082 0.9456845

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1. A set of reference genes for the normalization of gene expression analysis data from blood samples of a patient, wherein the set of reference genes comprises the following RNA sequences: SEQ ID NO: 87, SEQ ID NO: 89, SEQ ID NO: 90, SEQ ID NO: 91, SEQ ID NO: 93, SEQ ID NO: 95, and SEQ ID NO:
 96. 2. A set of primers derived from the set of reference genes according to claim 1, for the normalization of gene expression analysis data based on nucleic acid amplification, from blood samples of a patient, wherein the set of primers comprises the following DNA sequences: SEQ ID NO: 8 to SEQ ID NO:
 21. 3. A set of probes derived from the set of reference genes according to claim 1, for the normalization of gene expression analysis data from blood samples of a patient, wherein the set of probes comprises the following DNA sequences: SEQ ID NO: 1 to SEQ ID NO: 7, and/or their complementary nucleic acid sequences.
 4. A method for the normalization of gene expression analysis data with the aid of a set of control nucleic acids, comprising: a) carrying out at least one gene expression analysis assay in vitro on a set of test nucleic acids in blood samples of a patient; b) examining a set of control nucleic acids jointly in the same assay as a basis for the normalization of the gene expression analysis data of the samples to be examined, wherein the set of control nucleic acids is selected from the set of reference genes according to claim 1 the set of primers according to claim 2, or the set of probes according to claim 3, c) detecting signals from the gene expression analyses which reflect the degree of gene expression of a plurality of genes and of the set of control nucleic acids; d) subjecting the signal data obtained in step c) to a mathematical transformation in order to at least weaken the technical variability of the signal data; and e) normalizing thereby the transformed signal data of the samples to be examined.
 5. The method according to claim 4, wherein the mathematical transformation of the signal data is carried out by means of the arsinh or by means of a logarithmic approach.
 6. The method according to claim 4, wherein the gene expression assay is selected from: a) isolation of nucleic acids from a blood sample; b) co-amplification of a set of control nucleic acids and of the nucleic acids to be tested; and c) probe hybridization.
 7. The method according to claim 6, wherein the nucleic acids comprise mRNA or microRNA.
 8. The method according to claim 4, wherein the nucleic acids are amplified by means of PCR, real-time PCR, NASBA, TMA, or SDA.
 9. The method according to claim 6, wherein the expression values of the control and test nucleic acids are determined by means of hybridization methods.
 10. The method according to claim 4, wherein the measurement of the expression values of the control and/or test nucleic acids takes place in solution or on nucleic acids immobilized on a support.
 11. The method according to claim 10, wherein the support is a microarray, particle, bead, glass, metal, or membrane.
 12. The method according to claim 10, wherein the control and/or test nucleic acids are indirectly coupled to the support through other binding partners.
 13. The method according to claim 4, wherein the expression values of the control and test nucleic acids determined in vitro from a patient sample are used as input parameters for the production of software for the description of a patient's individual prognosis, for diagnostic purposes, for therapy decisions, and/or patient data management systems.
 14. A method as in claim 4, wherein the method for normalization of Rene expression analysis data involves the diagnosis of disorders involving systemic immune reaction.
 15. The method use according to claim 14, wherein the disorders are selected from: sepsis, severe sepsis, septic shock, or multiple organ failure.
 16. The method use according to claim 14 in a method for in-vitro diagnosis of SIRS, sepsis, severe sepsis, septic shock, or multiple organ failure in an individual by using sets of control nucleic acids and test nucleic acids having an expression that is specific for SIRS or sepsis, comprising the following steps: a) concurrent isolation of the control and test nucleic acids from a sample of the individual; b) in a given case, amplification of the control and test nucleic acids; c) determination of the expression values of the control and test nucleic acids; d) a normalization of the gene expression of the test nucleic acids based on the expression values of the control nucleic acids; and e) determination whether the noraialized expression values of the test nucleic acid have reached a specific value for SIRS, sepsis, severe sepsis, septic shock, or multiple organ failure.
 17. The method according to claim 12, wherein the binding partners are antibodies, antigens, oligonucleotides, molecular beacons, or enzymes. 